在python中查找与列表的col2中的值相关的col1中的最大值

pandas 很好,但你可以 max 和 lambda :

men = max(data, key=lambda x: x[1] if x[0] == 'men' else 0)
women = max(data, key=lambda x: x[1] if x[0] == 'women' else 0)
people = max(data, key=lambda x: x[1] if x[0] == 'people' else 0)

您可以使用 pandas 包装。 通过定义数据框:

import pandas as pd
df = pd.DataFrame([['men', 2, '1945-Truman.txt'],
                   ['women', 2, '1945-Truman.txt'],
                   ['people', 10, '1945-Truman.txt'],
                   ['men', 12, '1946-Truman.txt'],
                    ['women', 7, '1946-Truman.txt'],
                   ['people', 49, '1946-Truman.txt'],
                   ['men', 7, '1947-Truman.txt'],
                   ['women', 2, '1947-Truman.txt'],
                   ['people', 12, '1947-Truman.txt'],
                   ['men', 4, '1948-Truman.txt'],
                   ['women', 1, '1948-Truman.txt'],
                   ['people', 22, '1948-Truman.txt'],
                   ['men', 2, '1949-Truman.txt'],
                   ['women', 1, '1949-Truman.txt'],
                   ['people', 15, '1949-Truman.txt'],
                   ['men', 6, '1950-Truman.txt'],
                   ['women', 2, '1950-Truman.txt'],
                   ['people', 15, '1950-Truman.txt'],
                   ['men', 8, '1951-Truman.txt'],
                   ['women', 2, '1951-Truman.txt'],
                   ['people', 9, '1951-Truman.txt'],
                   ['men', 3, '1953-Eisenhower.txt'],
                   ['women', 0, '1953-Eisenhower.txt'],
                   ['people', 17, '1953-Eisenhower.txt']])

然后

df.groupby([0], sort=False)[1].max()

回来

0 
men       12
women      7
people    49
Name: 1, dtype: int64

这就是你想要的吗?

如果您使用的列表包括:

lst=[['men', 2123, '1945-Truman.txt'],
['women', 2, '1945-Truman.txt'],
['people', 10, '1945-Truman.txt'],
['men', 12, '1946-Truman.txt'],
['women', 7, '1946-Truman.txt'],
['people', 49, '1946-Truman.txt'],
['men', 7, '1947-Truman.txt'],
['women', 2, '1947-Truman.txt']]

然后可以使用以下代码。

max_men=0
max_women=0
max_people =0
for item in lst:
    if((item[0]=="men") and (item[1]>max_men)):
        max_men=item[1]
    elif((item[0]=="women") and (item[1]>max_women)):
        max_women=item[1]
    elif((item[0]=="people") and (item[1]>max_people)):
        max_people=item[1]

print max_men
print max_women
print max_people

这将进入名为 lst 并为男人、女人和人们找到最大的价值。

您可以创建第一列的集合,然后找到最大值:

data = [
    ['men', 2, '1945-Truman.txt'],
    ['women', 2, '1945-Truman.txt'],
    ...
]

keys = set([col[0] for col in data])

for k in keys:
        print (k, max([col[1] for col in data if col[0] == k]))

返回值:

women 7
people 49
men 12

您可以使用 itertools.groupby :

import itertools
new_data = [(a, list(b)) for a, b in itertools.groupby(sorted(data, key=lambda x:x[0]), key=lambda x:x[0])]
new_final_data = [max(b, key=lambda x:x[1]) for a, b in new_data]

输出:

[['men', 12, '1946-Truman.txt'], ['people', 49, '1946-Truman.txt'], ['women', 7, '1946-Truman.txt']]

或者,每个键都有一个字典,每个键的类型为:

new_final_data = {a:max(b, key=lambda x:x[1]) for a, b in new_data}

输出:

{'women': ['women', 7, '1946-Truman.txt'], 'men': ['men', 12, '1946-Truman.txt'], 'people': ['people', 49, '1946-Truman.txt']}

您可以使用 pandas 我想是吧 数据 是一个列表:

import pandas as pd

df = pd.DataFrame(data)

df.loc[df.groupby([0])[1].idxmax()]

        0   1                2
3     men  12  1946-Truman.txt
5  people  49  1946-Truman.txt
4   women   7  1946-Truman.txt

对于相同格式的结果:

df.loc[df.groupby([0])[1].idxmax()].values.tolist()

[['men', 12, '1946-Truman.txt'], ['people', 49, '1946-Truman.txt'], ['women', 7, '1946-Truman.txt']]

men = [t for t in yourlist if t[0] == 'men']
women = [t for t in yourlist  if t[0] == 'women']
people = [t for t in yourlist  if t[0] == 'people']
sorted(men, key=operator.itemgetter(1), reverse=True)[0][1]
sorted(women, key=operator.itemgetter(1), reverse=True)[0][1]
sorted(people, key=operator.itemgetter(1), reverse=True)[0][1]